PROJECT SUMMARY/ABSTRACT The goal of Core C is to provide high-throughput production and analysis of AML genomic and epigenomic sequence data for all four projects in this PPG. This includes sequencing, somatic and germline variant detection and validation, and integration of many data types. This will be achieved by generating high-quality DNA and RNA sequencing data and analyzing it using cutting-edge algorithms and techniques. Specific Aim/Core Service 1: (Sequence Production) Sequencing of samples in Core C will take place using the Illumina HiSeqX, 4000, and NovaSeq platforms. The data produced in Core C will be comprehensive: whole genome, exome, and capture validation for DNA, as well as error-corrected sequencing, single-cell RNA-seq, total and small RNA-seq, whole genome bisulfite sequencing, and other custom epigenetic analyses. These data will be processed through state-of-the-art genomic pipelines to produce primary results like sequence alignments and variant calls. Specific Aim/Core Service 2: (Bioinformatic Analysis) These pipelines provide a starting point for the detailed, novel, and iterative analyses which will take place in Core C and are foundational for each project. Project 1 will require integrative analysis of genomic and epigenomic (transcriptome, scRNA-Seq, WGBS) data to better define the events that drive initiation, progression, and relapse in samples with and without DNMT3A mutations. In Project 2, we will leverage our experience in immunogenomics to define minor histocompatibility antigens that mediate allo-transplant response, and characterize the genetic and epigenetic changes that drive relapse in a mouse model of transplantation. In Projects 3 and 4, we will utilize enhanced WGS, error-corrected sequencing, bulk RNA-seq, scRNA-seq, and phased-read data to define the mechanisms that drive subclonal expansion and progression from MDS to sAML (Project 3), or the specific effects of TP53 mutations on the development of aneuploid AML (Project 4). Answering the questions outlined in these projects requires deep integrative analysis that goes far beyond the simple mutation counting that was a hallmark of previous genomic studies. This requires common infrastructure, comprehensive databases, and extensive expertise that will be provided by tight integration between project leadership and the scientists in Core C.